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[return to "Measuring the impact of AI on experienced open-source developer productivity"]
1. nestor+3c[view] [source] 2025-07-10 17:42:34
>>dheera+(OP)
One thing I could not find on a cursory read is how used were those developers to AI tools. I would expect someone using those regularly to benefit while someone who only played with them a couple of time would likely be slowed down as they deal with the friction of learning to be productive with the tool.
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2. uludag+rf[view] [source] 2025-07-10 17:59:13
>>nestor+3c
In this case though you still wouldn't necessarily know if the AI tools had a positive causal effect. For example, I practically live in Emacs. Take that away and no doubt I would be immensely less effective. That Emacs improves my productivity and without it I am much worse in no way implies that Emacs is better than the alternatives.

I feel like a proper study for this would involve following multiple developers over time, tracking how their contribution patterns and social standing changes. For example, take three cohorts of relatively new developers: instruct one to go all in on agentic development, one to freely use AI tools, and one prohibited from AI tools. Then teach these developers open source (like a course off of this book: https://pragprog.com/titles/a-vbopens/forge-your-future-with...) and have them work for a year to become part of a project of their choosing. Then in the end, track a number of metrics such as leadership position in community, coding/non-coding contributions, emotional connection to project, social connections made with community, knowledge of code base, etc.

Personally, my prior probability is that the no-ai group would likely still be ahead overall.

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